654 Software Engineering Manager Data Ai jobs in Chicago,IL

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Associate, AI Engineer

KPMG

Chicago, IL 60629

Onsite

Minimum one years of recent professional or academic experience in AI/ML, data science, software engineering, or cloud technologies
Bachelor's degree from an accredited college or university in computer science, data science, engineering, or related field
Experience with at least one major cloud AI platform (Azure AI, AWS AI/Bedrock, or Google Cloud Vertex AI)
Proficiency in Python or another programming language commonly used in AI/ML
Familiarity with conversational AI frameworks (LLMs, chatbots, virtual assistants, agents) and APIs
Strong analytical skills and attention to detail with the ability to work in a team-based, client-focused environment
Ability to travel as required
Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future; KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity

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Construction Estimating Manager, AMER Data Center Construction

Amazon Data Services

Chicago, IL 60604

OnsiteHealth InsurancePaid Time OffRetirement Benefit

Experience in MS Excel, Word, and Windows Operating Systems
5+ years of construction or project management experience
Bachelor's Degree in Construction Management, Civil Engineering, Quantity Surveying, Engineering, or 5+ years of relevant experience.
Experience in Conceptual Estimating and Hard Bidding for ground-up commercial construction projects.
Proven track record of creating and releasing high-quality, consistent documentation for processes, standards, and procedures.
Be available to travel up to 20% of the time to support project and program needs.

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Director, AI Engineer

KPMG

Chicago, IL 60629

OnsiteHealth InsuranceRetirement Benefit

Minimum eight years of recent experience in AI/ML, data analytics, and cloud technology, including leadership roles in consulting or technology organizations; AI certifications (for example: Professional AI Architect, Machine Learning Engineer) or equivalent are a plus
Advanced degree from an accredited college or university in computer science, data science, engineering, or related field preferred; minimum of a Bachelor's degree from an accredited college or university is required
Deep knowledge and hands-on experience with Microsoft, AWS, and/or Google Cloud's AI ecosystem (including agent build functionality) to design and orchestrate intelligent multi-agent systems such as chatbots and virtual assistants that handle complex, dynamic tasks and conversations
Proficient in architecting and implementing AI-powered workflow solutions using Microsoft, AWS, or Google Cloud services (For example: Foundry, Bedrock, Vertex AI), with capabilities in defining blueprints and technical requirements for scalable, automated systems with expertise in agentic AI and automation
Skilled in designing multi-agent conversational AI systems integrated with enterprise applications (CRM, ERP), enhancing customer engagement through smart chatbots and virtual agents to improve user experience and operational efficiency; experienced in conversational AI integration
Deep understanding of scaling AI-driven solutions, ethical AI, and MLOps practices for maintaining models; ability to bring industry consulting insights with a balance of technical and business acumen to deliver strategic, value-driven AI solutions; In-depth knowledge of AI orchestration and best practices
Travel as needed
Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future; KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

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Business Development Manager - Geotech Construction

GeoStabilization International

Chicago, IL 60629

RemoteUrgently HiringHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Civil Engineering, Geology, or related field.
1+ years in technical sales, business development, or client-facing engineering roles (geotechnical or heavy civil preferred).
Strong foundation in geotechnical design principles and constructability.
Ability to operate effectively in fast-paced, deadline-driven environments.

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Manager of Transmission Line Engineering

Leidos

Chicago, IL 60606

RemoteFlexible SchedulePaid Time OffRetirement Benefit

Bachelor's degree in Civil, preferred, or Mechanical Engineering with twelve plus (12+) years of relevant experience in the design of high voltage electric utility transmission systems.
Professional Engineering Registration in at least one U.S. state or equivalent.
Experience with the following: PLS-CADD, POLE, TOWER, SAG10, LPILE and/or FAD, and Microsoft Office suite.
The candidate will apply NESC, ASCE, ACI, NEC, and other applicable standards in the engineering anddesign of all types of capital and maintenance projects from 34.5 kV to 765 kV.
Work effectively in a team environment; can also work independently.

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ResumeLibrary

Implementation Manager – Personalization & Customer Data Platforms (Sitecore Preferred)

BrainTrust

Chicago, IL 60601

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Engineering, Sr Manager

Constellation Energy

Berwyn, IL 60402

~ 20 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Engineering (Chemical, Civil/Structural, Electrical, Industrial, Mechanical or Nuclear) or related science OR Active/Inactive Senior Reactor Operator (SRO) license
10 years of overall related experience
Maintain minimum access requirement or unescorted access requirements, as applicable, and favorable medical examination and/or testing in accordance with position duties
Supervisory or managerial experience

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Executive Partner, Artificial Intelligence Advisory/ AI Strategist

Gartner

Chicago, IL 60601

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Senior GRC Advisor - Data & AI Governance

BMO Financial

Chicago, IL 60604

OnsiteEducation AssistanceHealth InsuranceRetirement Benefit

Data and AI Governance experience
Risk management experience.
CDMP and/or AIGP certifications.
Typically, 5 - 7 years of relevant experience in governance, risk, compliance, data governance, AI governance, risk management, audit, or related disciplines, with a strong focus on advisory and oversight activities.
Strong knowledge of Data and AI governance risk and regulatory requirements, including data privacy, data quality, model risk, and emerging AI governance considerations.
Solid understanding of applicable regulations, industry standards, and control frameworks relevant to enterprise risk management and the data and AI lifecycle.
Experience supporting risk assessments (e.g., PSPRA, RCRA, process risk and control assessments), including advising on risk identification, control considerations, and Key Risk Indicators (KRIs).
Strong analytical and critical-thinking skills, with the ability to assess governance and control alignment, identify gaps, and articulate risk implications.
Effective communication, collaboration, and stakeholder management skills, with the ability to influence across first- and second-line functions.
Ability to work independently, exercise sound judgment, and appropriately escalate governance or risk concerns.
CDMP - Certified Data Management Professional (by DAMA)
CRISC - Certified in Risk and Information Systems Control (by ISACA) OR CGRC - Certified in Governance, Risk and Compliance (by ISC2)

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Process Simulation Twin & Optimization Engineer - Refinery Experience Only

Aramco

Chicago, IL 60290

Onsite

You must hold a Bachelor's degree in Chemical Engineering.
You will have a minimum of 15 years of experience in Process Simulations, Online Modeling, or Real-Time Optimization (preferably ROMeo).
You will be able to Demonstrate expertise in process engineering and flowsheet-based processes simulation.
You will have comprehensive understanding of refinery facilities, feedstock/product movements, margins, giveaways, process yields, and mass and energy balances.
Demonstrated experience connecting simulations to live data sources (Data Historians, OPC, etc.).
Strong understanding of data reconciliation, model tuning, and dealing with gross errors in industrial data is also required.

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